AI Ethics & Governance
Top Stories
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Feature
18 Sep 2026
AI extinction: What IT leaders need to know -- and do -- now
AI extinction concerns are growing among experts, but for enterprises, the focus should be on governance, accountability and risk management to prevent operational failures. Continue Reading
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News
18 Sep 2026
AI agent autonomy puts CIO controls to the test
As AI leaders warn capabilities are advancing faster than safeguards, CIOs face a more immediate question: how much authority to give enterprise agents. Continue Reading
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News
15 Dec 2020
DataRobot releases new feature to detect AI bias
DataRobot is the latest AI vendor to address AI bias, releasing a new feature to help organizations detect and prevent bias in their models. Continue Reading
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News
08 Dec 2020
Amazon SageMaker Clarify aims to mitigate bias in machine learning
AWS looks to tackle machine learning bias with a new a new tool that works with Amazon SageMaker products to help developers and users better detect and eliminate AI bias. Continue Reading
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News
04 Dec 2020
Hundreds support former Google AI ethics researcher Timnit Gebru
A prominent AI ethics researcher said she was unfairly fired by Google after sending an email to colleagues critical of the way Google treats women and people of color. Continue Reading
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Feature
26 Oct 2020
Insurance provider uses AI for legal to manage contracts
The legal team at Asurion, a major insurance provider, kept its documents spread out across filing cabinets, hard drives and the cloud. It turned to an AI platform to better manage them. Continue Reading
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Feature
09 Oct 2020
Establishing AI governance in a business
It's hard to ethically manage data for AI models, but AI governance, as well as a strong ethics framework, can help enterprises effectively manage data and models. Continue Reading
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Feature
25 Sep 2020
The deepfake 2020 election threat is real, but containable
Disinformation could harm the 2020 presidential election, and technology simply isn't advanced enough to detect manipulated content, especially deepfakes. Continue Reading
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News
03 Sep 2020
Microsoft deepfake software combats election propaganda
Ahead of the 2020 United States presidential election, Microsoft released Video Authenticator, an AI-powered tool to help identify deepfake images and videos. Continue Reading
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Feature
31 Aug 2020
Responsible AI champions human-centric machine learning
Encompassing ethics, transparency and human centricity, responsible AI is an effective approach to deploying machine learning models and achieving actionable insights. Continue Reading
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Feature
27 Aug 2020
It's time to address AI ethics
Enterprises need to focus on creating and adopting AI ethical guidelines, especially for emerging technologies such as facial recognition and home assistants. Continue Reading
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Feature
25 Aug 2020
Bias in machine learning examples: Policing, banking, COVID-19
Human bias, missing data, data selection, data confirmation, hidden variables and unexpected crises can contribute to distorted machine learning models, outcomes and insights. Continue Reading
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Opinion
17 Aug 2020
Does technology increase the problem of racism and discrimination?
According to a publication from the MIT Technology Review, technology promotes racism. Most facial recognition algorithms discriminate against the Black population. And even certain concepts or technological terminology tend to be offensive, highlighting "white supremacy." Continue Reading
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Tip
11 Aug 2020
Data science's ongoing battle to quell bias in machine learning
Machine learning expert Ben Cox of H2O.ai discusses the problem of bias in predictive models that confronts data scientists daily and his techniques to identify and neutralize it. Continue Reading
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Feature
30 Jun 2020
Understanding how deep learning black box training creates bias
Bias in AI is a systematic issue that derails many projects. Dismantling the black box of deep learning algorithms is crucial to the advancement and deployment of the technology. Continue Reading
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News
29 Jun 2020
IBM donates AI ethics tools to Linux Foundation
IBM donates open source toolkits AI Fairness 360, Adversarial Robustness 360 and AI Explainability 360 to the Linux Foundation amid calls for more ethical AI. Continue Reading
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Feature
29 May 2020
Contact tracing apps seem effective, but have privacy concerns
Contact tracing mobile applications appear to offer an easier, safer way to track where an infected person has been, but technology could cross a data privacy boundary. Continue Reading
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News
19 May 2020
Pegasystems releases Ethical Bias Check to cut down on AI bias
Pegasystems has embedded a new tool to combat AI bias in its Pega Customer Decision Hub. The tool can alert users to potential biases before they deploy system changes. Continue Reading
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News
08 May 2020
Automated data governance vendor Immuta gets key update
An update to Immuta's automated data governance enabled one of its users to better anonymize its consumers' data and control who has access to it. Continue Reading
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Feature
24 Apr 2020
Safety vs. privacy in the age of coronavirus raises tech questions
To slow the spread of the coronavirus, governments and organizations are using contact tracing and thermal imaging for fever detection, but these methods carry privacy concerns. Continue Reading
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Feature
21 Apr 2020
4 explainable AI techniques for machine learning models
At its core, AI is a complex modeling process with layers of information. In order to be able to explain the algorithm's decision-making process, start with its input data. Continue Reading
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Feature
15 Apr 2020
Here's how one lawyer advises removing bias from AI
Avoiding bias in AI applications is one of the central challenges in using the technology. Here's some advice on deploying AI technologies in a way that is fair. Continue Reading
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Feature
02 Apr 2020
Using AI in AML fights fraud while protecting privacy
Money laundering and fraud remain a risk for financial institutions, but AI can act as a useful tool against a constantly evolving financial enemy. Continue Reading
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Feature
04 Mar 2020
The state of AI defined by global adoption and regulation
Cognilytica reports on AI adoption by both countries and companies across the globe, as well as the former's overall strategies and regulation frameworks. Continue Reading
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News
02 Mar 2020
The pope, with Microsoft and IBM, calls for AI ethics
The Pontifical Academy for Life has issued new guidelines for ethical AI that call for artificial intelligence technology to be explainable, trusted and secure. Continue Reading
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News
20 Feb 2020
EU AI regulation guidelines worry vendors
The EU released AI regulation guidelines that demand AI systems in high-risk areas are transparent and have human oversight. Some vendors are worried. Continue Reading
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News
07 Feb 2020
IBM's Policy Lab calls for AI regulation
Launched during the Davos World Economic Forum, IBM's Policy Lab seeks to unite governments and businesses on creating and adopting more regulation of AI. Continue Reading
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Feature
27 Dec 2019
The complex nature of regulating AI
Regulating AI is a difficult task because the technology changes rapidly. Governments must be able to employ preventative regulation to prevent any misuse. Continue Reading
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Feature
24 Dec 2019
UX defines chasm between explainable vs. interpretable AI
From deep learning to simple code, all algorithms should be transparent. The frameworks of AI interpretability and explainability aim to make machine learning understandable to humans. Continue Reading
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Feature
12 Dec 2019
AI trends 2020 outlook: More automation, explainability
Top AI trends for 2020 are increased automation to extend traditional RPA, deeper explainable AI with more natural language capacity, and better chips for AI on the edge. Continue Reading
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News
06 Dec 2019
AWS, NFL machine learning partnership looks at player safety
A new AWS and NFL partnership aims to use AI and machine learning to reduce the risk of injuries to players. The partnership builds off of the companies' Next Gen Stats agreement. Continue Reading
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News
22 Nov 2019
Google Cloud Explainable AI aims to clear up outputs
A new Google product suite enables users to create and deploy more interpretable machine learning models with output visualizations, feature attribution and evaluation tools. Continue Reading
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News
14 Nov 2019
Anaheim PD explores facial recognition for law enforcement
Using a facial recognition platform from Veritone, the Anaheim Police Department can more quickly identify suspects captured on camera by comparing photos with booking photos. Continue Reading
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Feature
08 Nov 2019
Training data in facial recognition use cases reveals bias
Applications of facial recognition technology show incredible promise in law enforcement and personal privacy, but the risks are holding enterprises back from adoption. Continue Reading
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News
10 Oct 2019
As more push for explainable AI, companies add features
As businesses demand more explainable AI, vendors such as IBM and DarwinAI are introducing new features to help break down for business users how AI systems work. Continue Reading
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Feature
07 Oct 2019
Government AI strategy includes tech transfer to private sector
The Department of Energy's chief commercialization officer works with the DoE's national laboratories on transferring AI and other technologies to the private sector. Continue Reading
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Feature
03 Oct 2019
Ethical concerns of AI call growing adoption into question
AI tools are getting easier to use every day, putting powerful tools into the hands of potentially malicious users. The time to think about the ethics of AI advances is now. Continue Reading
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News
03 Oct 2019
Energy secretary Rick Perry touts U.S. government AI efforts
The U.S. government is ramping up AI research and development efforts to try to stay ahead of China in both public and private sector AI efforts. Continue Reading
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Feature
23 Sep 2019
Clashes between AI and data privacy affect model training
Enterprises' lax data rules reveal weaknesses around AI and model training -- particularly machine learning's reliance on unrestrained big data collection. Continue Reading
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News
19 Sep 2019
Organizations hire ethicists for AI ethical concerns
As organizations wrestle with AI ethical concerns, they need to create AI ethicist roles or develop teams to consider issues around data governance, data privacy and AI ethics. Continue Reading
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Feature
16 Sep 2019
Collaborative robots' safety stalls enterprise implementation
Cobots are promising big gains, especially in enterprises utilizing manual labor. However, due to a number of safety concerns, human workers are still at risk. Continue Reading
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News
28 Aug 2019
Microsoft India AI workshops to upskill government employees
Microsoft India partnered with the government of India to launch a new training program for government employees on AI, data governance and cloud computing. Continue Reading
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Feature
28 Aug 2019
Enterprises work toward AI trust and transparency
If ignored, a lack of trust in AI algorithms could diminish user adoption. To remedy this risk, enterprises are working to make their applications more transparent and explainable. Continue Reading
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News
09 Aug 2019
IBM interprets machine models with AI Explainability kit
IBM's open source AI Explainability 360 toolkit packages algorithms and training examples to help humans better understand the decision-making process of machine learning models. Continue Reading
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News
08 Aug 2019
Enterprises should start developing an AI ethics framework
As enterprises begin to deploy AI, they should focus on AI and ethics issues, as well as data privacy, and begin to create policies and guidelines around them. Continue Reading
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Feature
01 Aug 2019
Use of AI in government makes agencies smarter
Government agencies are starting to embrace some of the same AI technologies that typical enterprises use, and many are finding increased efficiencies along the way. Continue Reading
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Feature
31 Jul 2019
AI in law enforcement is growing, but needs work
AI for police includes numerous different analytics, machine learning and natural language processing technologies, including facial recognition and automated transcription tools. Continue Reading
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Feature
18 Jul 2019
Enterprise consumer relationships are building trust in AI
Transparency is an increasingly important component of consumer trust. If you want to win over consumers whose data is being collected, start with explainability and collaboration. Continue Reading
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Feature
16 Jul 2019
How AI in physical security makes public places safer
Deep learning-based tools are increasingly finding a home in physical security to enhance the protection of real-world assets and make public spaces safer. Continue Reading
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Feature
11 Jul 2019
AI in the legal industry focuses on augmenting research
From billable time invoice generation to patent attribute data mining, the implementation of AI in law firms has aided in reducing low-value, time-consuming paralegal work. Continue Reading
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News
27 Jun 2019
Use of AI in government still lags
Adoption of AI in government might lag behind the business world, but some agencies within the government hope to make more use of AI. Continue Reading
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News
26 Jun 2019
Working toward explainable AI
Many constituencies are on a push toward explainable AI algorithms, as AI technologies become more widespread, powerful and relied upon than ever before. Continue Reading
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Feature
12 Jun 2019
How data privacy and marketing coexist when influencing the public
The author of a new book on the intersection of advertising and marketing with AI and data privacy talks about influencing the public with technology. Continue Reading
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Feature
29 May 2019
Human rights advocate talks GDPR, AI and data privacy laws
Human rights advocate Bjørn Stormorken talks about the importance of data privacy laws, and why stronger laws and more data literacy are necessary today. Continue Reading
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Feature
16 Apr 2019
AI bias, for good or ill
Bias in AI algorithms can produce harmful results, but it can also help train models. This third part of a three-part series on AI ethics explains the pros and cons of AI bias. Continue Reading
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Feature
09 Apr 2019
How to address the hidden risks of algorithmic decision making
From biased customer interactions to harmful treatment recommendations, some risks of automated decisions have yet to be resolved. A Wharton School professor has a way out. Continue Reading
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Feature
08 Apr 2019
3 ways to create an AI ethics framework for responsible tech
AI can often reflect the biases and limits of its human developers. Experts say diversity, review boards and a strong AI ethics framework will lead the way toward ethical AI. Continue Reading
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Feature
29 Mar 2019
Address anonymity and data privacy in chatbot security
A key to successful enterprise chatbot security is to program your chatbot to recognize personal or sensitive information and treat it accordingly. Continue Reading
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Feature
12 Mar 2019
AI in accounting boosts compliance and fraud detection
Accounting and finance teams are using AI tools to speed document review and other error-prone processes, which gives a boost to fraud detection and compliance efforts. Continue Reading
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Feature
27 Feb 2019
Trump's AI executive order glosses over data privacy, funding
Trump released his AI executive order two weeks ago, and researchers are continuing to analyze its potential impact on the industry. One thing is certain: AI is about to change. Continue Reading
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Feature
14 Feb 2019
Interpretable AI has benefits beyond compliance
Making AI models more interpretable has a wide range of benefits and shouldn't just be thought of as a compliance exercise, experts at the H2O World conference said. Continue Reading
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Feature
11 Feb 2019
AI regulation stirs as unrestricted AI booms in China
Governments need to start regulating AI as the technology advances, experts say in part one of a three-part series on AI ethics issues around regulation, control and bias. Continue Reading
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Feature
18 Dec 2018
Explainability is no solution to problem of bias in AI
Explainability has been touted as a solution to the problem of biased AI models, but experts say that approach only gets you part of the way to bias-free applications. Continue Reading
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Feature
28 Nov 2018
Compliance.ai uses Tibco Cloud Mashery for API mastery
Compliance.ai, a compliance and regulatory management platform vendor, uses Tibco Mashery to help manage and compile many different APIs and data sources. Continue Reading
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Feature
14 Aug 2018
Algorithmic bias top problem enterprises must tackle
No enterprise today would roll out an obviously biased AI tool, but many remain unaware of the risks of unconscious bias in algorithms, which can produce equally dangerous results. Continue Reading
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Feature
30 May 2018
Addressing the ethical issues of AI is key to effective use
Enterprises must confront the ethical implications of AI use as they increasingly roll out technology that has the potential to reshape how humans interact with machines. Continue Reading
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Podcast
15 May 2018
Avoid bias in algorithms for best AI results
In this podcast, we examine leading thoughts on the problem of AI bias and how to mitigate some of the most common sources of unfair treatment of users of AI applications. Continue Reading
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Feature
25 Apr 2018
GDPR regulations put premium on transparent AI
As the EU's GDPR regulations go into effect, enterprises must focus on building transparency in AI applications so that algorithms' decisions can be explained. Continue Reading
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Podcast
13 Apr 2018
CTO Simon Crosby explains edge intelligence, talks AI uses and risks
Edge intelligence is the newborn child of edge analytics and machine learning. In this podcast, CTO Simon Crosby explains the tech and discusses AI uses, data breaches and more. Continue Reading
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Feature
02 Apr 2018
How to keep your implementation of AI free from algorithm bias
When implementing AI, it's important to focus on the quality of training data and model transparency in order to avoid potentially damaging bias in models. Continue Reading
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News
02 Mar 2018
Expert panel warns developers to beware of AI bias
Despite new development tools to build AI applications, developers must be wary of bias creeping into their systems. Continue Reading
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Feature
15 Feb 2018
Big data throws bias in machine learning data sets
AI holds massive potential for good, but it also amplifies negative outcomes if data scientists don't recognize data biases and correct them in machine learning data sets. Continue Reading